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2nd Sem > Information Management - 2 > Flashcards

Information Management - 2 Flashcards

1
Q

Data model

A

refers to representation of complex real-world data structures

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2
Q

Model

A

abstraction of real-world object/event

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3
Q

data modeling is

A

progressive and iterative

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4
Q

The Importance of Data Models

A
  1. facilitates interaction between user, applicationnprogrammer, and designer
  2. every end-user has their own different views and needs
  3. data model oragnizes data for various users
  4. data model is abstraction
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5
Q

Entity

A

anything about which data are to be collected and stored

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6
Q

Attributes

A

characteristic of an entity

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7
Q

Relationship

A

describes association of the entities
* One-to-many (1:M) relationship
* Many-to-many (M:N or M:M) relationship
* One-to-one (1:1) relationship

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8
Q

Constraint

A

restriction placed on data

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9
Q

Business Rules

A
  • Descriptions of policies, procedures, or principles within a specific organization
    -Apply to any organization that stores and uses data to generate information
  • Description of operations to create/enforce actions within an organization’s environment
    -Must be in writing and kept up to date
    -Must be easy to understand and widely disseminated
  • Describe characteristics of data as viewed by the company
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10
Q

Sources of business rules

A
  1. Company manager
  2. policy maker
  3. department manager
  4. written documentation
    * Procedures
    * Standardization
    * Operations manual
  5. Direct interview with the end-user
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11
Q

Dsicovering Business Rules

A
  1. Standardize company’s view of data
  2. Communications tool between users and designers
  3. Allow designer to understand the nature, role, and scope of data
  4. Allow designer to understand business processes
  5. Allow designer to develop appropriate relationship participation rules and constraints
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12
Q

Translating Business Rules into Data Model Components

A
  • Generally,** nouns** translate into entities
  • Verbs translate into relationships among entities
  • Relationships are bidirectional
  • Two questions to identify the relationship type:
  • How many instances of B are related to one instance of A?
  • How many instances of A are related to one instance of B?
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13
Q

Naming Conventions

A
  1. Naming occurs during translation of business rules to data model components
  2. Names should make the object unique and distinguishable from other objects
  3. Names should also be descriptive of objects in the environment and be familiar to users
  4. Proper naming:
    * facilitates communication between parties
    * promotes self-documentation
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14
Q

The Evolution of Data Models

A

https://images.slideplayer.com/25/8127133/slides/slide_9.jpg

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15
Q

The Hierarchical Model

A
  • The hierarchical model was developed in the 1960s to manage large amounts of data for manufacturing projects
  • Basic logical structure is represented by an upside-down “tree”
  • Hierarchical structure contains levels or segments
    a. Segment analogous to a record type
    b. Set of one-to-many relationships between segments
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16
Q

Network Model

A
  • created to represent complex data relationships more effectively than the hierarchical model
    -Improves database performance
    -Imposes a database standard
  • Resembles hierarchical model
    -However, record may have more than one parent
  • Collection of records in 1:M relationships
  • Set composed of two record types:
    Owner - Equivalent to the hierarchical model’s parent
    Member - Equivalent to the hierarchical model’s child
  • Concepts still used today:
    Schema- Conceptual organization of entire database as viewed by the database administrator
    Subschema -Database portion “seen” by the application programs
    Data management language (DML) -Defines the environment in which data can be managed
    Data definition language (DDL)-Enables the administrator to define the schema components
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17
Q

Schema

A

Conceptual organization of entire database as viewed by the database administrator

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18
Q

Subschema

A

Database portion “seen” by the application programs

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19
Q

Database Management Language (DML)

A

Defines the environment in which data can be managed

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20
Q

Database Definition Language (DML)

A

Enables the administrator to define the schema components

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21
Q

Disadvantages of the network model

A
  1. Cumbersome
  2. Lack of ad hoc query capability placed burden on programmers to generate code for reports
  3. Structural change in the database could produce havoc in all application programs
22
Q

Relational model

A
  • Developed by E.F. Codd (IBM) in 1970
  • Table (relations)
  • Matrix consisting of row/column intersections
  • Each row in a relation is called a tuple
  • Relational models were considered impractical in 1970
  • Model was conceptually simple at expense of computer overhead
23
Q

Relational data management system (RDBMS)

A
  • performs same functions as hierarical model
  • hides complexity from user
24
Q

Relational diagram

A

representation of entities, attributes, and relationship

25
Q

Relational table

A

collection of related entities

26
Q

SQL-based relational database application involves three parts

A

1. User interface
* Allows end user to interact with the data
2. Set tables stored in database
* Each table is independent from another
* Rows in different tables are related based on common values in common attributes
3. SQL Engine
* Executes all queries

27
Q

The Entity Relationship Model

A
  • widely accepted in data modeling
  • Introduced by Chen in 1976
  • graphical representtaion of entities and their relationship based on data structure
28
Q

Entity relationship diagram (ERD)

A
  • uses graphical representation to model database components
  • entity is mapped in relational table
29
Q

The Entity Relationship Model (cont’d.)

A
  • Entity instance (or occurrence) is row in table
  • Entity set is collection of like entities
  • ** Connectivity labels** types of relationships
  • Relationships are expressed using Chen notation
    -Relationships are represented by a diamond
    -Relationship name is written inside the diamond
  • Crow’s Foot notation used as design standard in this book
30
Q

object

A
  • contains operations
  • self-contained: building blocks for autonomous strcutures
  • abstraction of real-world entity
31
Q

The Object-Oriented (OO) Model

A

OODM (object-oriented data model) is the basis for OODBMS
Semantic data model

32
Q

Attributes

Object

A

describe object properties

33
Q

Objects that share similar characteristics

A

are grouped in a class

34
Q

Class

A

organized class hierarchy

35
Q

Class

A

organized class hierarchy

36
Q

Inheritance

A

object inherits methods and attributes of parent class

37
Q

UML

A
  • based on OO concepts that describe diagrams and symbols
    -Used to graphically model a system
38
Q

Extended relational data model (ERDM)

A
  • Semantic data model developed in response to increasing complexity of applications
  • Includes many of OO model’s best features
  • Often described as an object/relational database management system (O/RDBMS)
  • Primarily geared to business applications
39
Q

Extensible Markup Language (XML)

A
  • emerged as de facto standard
  • standard protocol for data exchange in systems and Internet service
40
Q

Internet revolution

A

created potential exchange critical business infromation

41
Q

The Future of Data Models

A
  1. Hybrid DBMS
  2. SQL Data Services
42
Q

Hybrid DBMS

A
  • Retain advantages of relational model
  • Provide object-oriented view of the underlying data
43
Q

SQL Data Services

A
  • Store data remotely without incurring expensive hardware, software, and personnel costs
  • Companies operate on a “pay-as-you-go” system
44
Q

Data Model: Characteristics

A
  • Conceptual simplicity with semantic completeness
  • Represent real-world as close as possible
  • Real-world transformation must comply with integrity and consistency characteristics
45
Q

Data Models: A Summary

A
  • Common characteristics:
  • Conceptual simplicity with semantic completeness
  • Represent the real world as closely as possible
    -Real-world transformations must comply with consistency and integrity characteristics
  • Each new data model capitalized on the shortcomings of previous models
  • Some models better suited for some tasks
46
Q

Database designer starts with

A

abstracted view and add detials

47
Q

Basic data modeling components

A
  1. Entities
  2. Attributes
  3. Relationships
  4. Constraints
48
Q

Hierarchical model, Network model, Relational Model

A
  • Set of one-to-many (1:M) relationships between a parent and its children segments
  • Uses sets to represent 1:M relationships between record types
  • Current database implementation standard
    ER model is a tool for data modeling
49
Q

Standard Planning and Requirement Committe (1970)
SPARC

A

Defined a framework for data modeling based on degrees of data abstraction (1970s):
* External
* Conceptual
* Internal

50
Q

External Model

A
  1. End users’ view of the data environment
  2. ER diagrams represent external views
  3. External schema: specific representation of an external view
    * Entities
    * Relationships
    * Processes
    * Constraints
  4. Easy to identify specific data required to support each business unit’s operations
  5. Facilitates designer’s job by providing feedback about the model’s adequacy
  6. Ensures security constraints in database design
    Simplifies application program development
51
Q

The Conceptual Model

A
  • Represents global view of the entire database
  • All external views integrated into single global view: conceptual schema
  • ER model most widely used
  • ERD graphically represents the conceptual schema
  • Provides a relatively easily understood macro level view of data environment
  • Independent of both software and hardware
    -Does not depend on the DBMS software used to implement the model
    -Does not depend on the hardware used in the implementation of the model
    -Changes in hardware or software do not affect database design at the conceptual level
52
Q

The Internal Model

A
  • Representation of the database as “seen” by the DBMS
  • Maps the conceptual model to the DBMS
  • Internal schema depicts a specific representation of an internal model
  • Depends on specific database software
    -Change in DBMS software requires internal model be changed
  • Logical independence: change internal model without affecting conceptual model

2nd Sem (21 decks)

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